It has been widely recognized that satellite remote sensing data have a great potential in retrieval of crop biophysical variable such as Leaf Area Index (LAI), vegetation canopy cover and fraction of absorbed photosynthetically active radiation (fAPAR), that are indicative of crop growth condition and yield formation. Unmanned Aerial Vehicle (UAV) data are popular in […]

The efficient monitoring of soil and crop parameters is essential for crop stress evaluation and yield forecast in agriculture, yet most remote sensing studies focus on regional-scale soil and crop parameters estimation using satellite data. Satellite remote sensing is difficult to obtain both high spatial and temporal resolution data with a low-cost in field-scale. Currently, […]

This study will focus on an alternative remote sensing method for crop long-term biomass monitoring and prediction of final yield using Unmanned Aerial Vehicle (UAV) based 3D point cloud data in Southwestern Ontario. Currently, biomass and yield are estimated from statistical and crop growth models. However, statistical models are only applicable for specific area or […]

A&L Canada Labs Inc. is developing a UAV (Unmanned Aerial Vehicle) or drone with a multi-spectral camera for various precision agriculture applications. The multi-spectral camera has 6 bands: one in the red band, one in the blue band, one in the green band, and three in the NIR regions. The scope of this project is […]